Ranking the spreading influence in complex networks

Abstract

Identifying the node spreading influence in networks is an important task to optimally use the network structure and ensure the more efficient spreading in information. In this paper, by taking into account the shortest distance between a target node and the node set with the highest $k$-core value, we present an improved method to generate the ranking list to evaluate the node spreading influence. Comparing with the epidemic process results for four real networks and the Barabási-Albert network, the parameterless method could identify the node spreading influence more accurately than the ones generated by the degree $k$, closeness centrality, $k$-shell and mixed degree decomposition methods. This work would be helpful for deeply understanding the node importance of a network.

6 pages, 3 figures

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Cited by in corpus (7)

• Vital nodes identification in complex networks
• Centrality measure based on continuous-time quantum walks and experimental realization
• Centrality Measures in Complex Networks: A Survey
• Weighted H-index for identifying influential spreaders
• Finding the proper node ranking method for complex networks
• Improving the accuracy of the k-shell method by removing redundant links-from a perspective of spreading dynamics
• Promotion and resignation in employee networks